IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v56y2018i16p5475-5494.html
   My bibliography  Save this article

Kitting optimisation in Just-in-Time mixed-model assembly lines: assigning parts to pickers in a hybrid robot–operator kitting system

Author

Listed:
  • Mohamed El Amine Boudella
  • Evren Sahin
  • Yves Dallery

Abstract

With increasing components’ variety in mixed-model assembly lines, industrials show interest in kitting operations using robots. This paper deals with a hybrid kitting system that consists of a robot and an operator working in series to deliver parts to a Just-In-Time mixed-model assembly line. We develop a mathematical model that optimally assigns stock keeping units to either the robot or the operator so that the cycle time of the overall system is optimised. To test the model, a case study from the automotive sector is presented and a sensitivity analysis is carried out on relevant system parameters.

Suggested Citation

  • Mohamed El Amine Boudella & Evren Sahin & Yves Dallery, 2018. "Kitting optimisation in Just-in-Time mixed-model assembly lines: assigning parts to pickers in a hybrid robot–operator kitting system," International Journal of Production Research, Taylor & Francis Journals, vol. 56(16), pages 5475-5494, August.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:16:p:5475-5494
    DOI: 10.1080/00207543.2017.1418988
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2017.1418988
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2017.1418988?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dieter Fiems, 2024. "Performance of a Synchronisation Station with Abandonment," Mathematics, MDPI, vol. 12(5), pages 1-12, February.
    2. Emilio Moretti & Elena Tappia & Martina Mauri & Marco Melacini, 2022. "A performance model for mobile robot-based part feeding systems to supermarkets," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 580-613, September.
    3. Yilmaz, Aysegul & Dora, Manoj & Hezarkhani, Behzad & Kumar, Maneesh, 2022. "Lean and industry 4.0: Mapping determinants and barriers from a social, environmental, and operational perspective," Technological Forecasting and Social Change, Elsevier, vol. 175(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:56:y:2018:i:16:p:5475-5494. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.